Biology subjects

Subramaniam, M.

Publications and source records attributed to Subramaniam, M..

7 recordsLinked to original sources

bioRxiv2018

Functional Interpretation of Single-Cell Similarity Maps

We present VISION, a tool for annotating the sources of variation in single cell RNA-seq data in an automated, unbiased and scalable manner. VISION operates directly on the manifold of cell-cell similarity and employs a flexible annotation approach that can operate either with or without preconceived stratification of the cells into groups or along a continuum. We demonstrate the utility of VISION using a relatively homogeneous set of B cells from a cohort of lupus patients and healthy controls and show that it can derive important sources of cellular variation and link them to clinical phenotypes in a stratification free manner. VISION produces an interactive, low latency and feature rich web-based report that can be easily shared amongst researchers.

bioinformatics↗

bioRxiv2018

GBAT: a gene-based association method for robust trans-gene regulation detection

Identification of trans-eQTLs has been limited by a heavy multiple testing burden, read-mapping biases, and hidden confounders. To address these issues, we developed GBAT, a powerful gene-based method that allows robust detection of trans gene regulation. Using simulated and real data, we show that GBAT drastically increases detection of trans-gene regulation over standard trans-eQTL analyses.

genetics↗

bioRxiv2018

Genetic and environmental perturbations lead to regulatory decoherence

Correlation among traits is a fundamental feature of biological systems. From morphological characters, to transcriptional or metabolic networks, the correlations we routinely observe between traits reflect a shared regulation that remains poorly understood and difficult to study. To address this problem, we developed a new and flexible approach that allows us to identify factors associated with variation in correlation between individuals. Here, we use data from three large human cohorts to study the effects of genetic variation and environmental perturbation on correlations among mRNA transcripts and among NMR metabolites. We first show that environmental exposures (namely, infection and disease) lead to a systematic loss of correlation, which we define as decoherence. Using longitudinal data, we show that decoherent metabolites are better predictors of whether someone will develop metabolic syndrome than metabolites commonly used as biomarkers of this disease. Finally, we show that correlation itself is a trait under genetic control: specifically, we mapped and replicated hundreds of correlation QTLs, which often involve transcription factors or their known target genes. Together, this work furthers our understanding of how and why coordinated biological processes break down, and highlights the role of decoherence in disease emergence.

genomics↗

bioRxiv2017

Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection

While the impact of common genetic variants on gene expression response to cellular stimuli has been analyzed in depth, less is known about how stimulation modulates the genetic control of isoform usage. Analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to viral infection and stimulation with type I interferon. We identified more than a thousand single nucleotide polymorphisms associated with isoform usage (isoQTLs), > 40% of which are independent of expression QTLs for the same gene. Compared to eQTLs, isoQTLs are enriched for splice sites and untranslated regions, and depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs in stimulated cells explain a significant proportion of the disease heritability attributed to common genetic variants. At the IRF7 locus, we found alternative promoter usage in response to influenza as a possible mechanism by which DNA variants previously associated with immune-related disorders mediate disease risk. At the ERAP2 locus, we shed light on the function of the major haplotype that has been maintained under long-term balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with absence of ERAP2 expression while the minor haplotype, known to increase Crohns disease risk, is associated with high ERAP2 expression. Surprisingly, in response to influenza infection, the major haplotype results in the expression of two uncharacterized, alternatively transcribed, spliced and translated short isoforms. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in the innate immune response, and in the case of ERAP2, may confer a historical fitness advantage in response to virus.

genomics↗

bioRxiv2017

Multiplexing droplet-based single cell RNA-sequencing using natural genetic barcodes

Droplet-based single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes from tens of thousands of cells. Multiplexing samples for single cell capture and library preparation in dscRNA-seq would enable cost-effective designs of differential expression and genetic studies while avoiding technical batch effects, but its implementation remains challenging. Here, we introduce an in-silico algorithm demuxlet that harnesses natural genetic variation to discover the sample identity of each cell and identify droplets containing two cells. These capabilities enable multiplexed dscRNA-seq experiments where cells from unrelated individuals are pooled and captured at higher throughput than standard workflows. To demonstrate the performance of demuxlet, we sequenced 3 pools of peripheral blood mononuclear cells (PBMCs) from 8 lupus patients. Given genotyping data for each individual, demuxlet correctly recovered the sample identity of > 99% of singlets, and identified doublets at rates consistent with previous estimates. In PBMCs, we demonstrate the utility of multiplexed dscRNA-seq in two applications: characterizing cell type specificity and inter-individual variability of cytokine response from 8 lupus patients and mapping genetic variants associated with cell type specific gene expression from 23 donors. Demuxlet is fast, accurate, scalable and could be extended to other single cell datasets that incorporate natural or synthetic DNA barcodes.

bioinformatics↗

bioRxiv2016

Discovery of an autoimmunity-associated IL2RA enhancer by unbiased targeting of transcriptional activation

The majority of genetic variants associated with common human diseases map to enhancers, non-coding elements that shape cell type-specific transcriptional programs and responses to specific extracellular cues 1-3. In order to understand the mechanisms by which non-coding genetic variation contributes to disease, systematic mapping of functional enhancers and their biological contexts is required. Here, we develop an unbiased discovery platform that can identify enhancers for a target gene without prior knowledge of their native functional context. We used tiled CRISPR activation (CRISPRa) to synthetically recruit transcription factors to sites across large genomic regions (>100 kilobases) surrounding two key autoimmunity risk loci, CD69 and IL2RA (interleukin-2 receptor alpha; CD25). We identified several CRISPRa responsive elements (CaREs) with stimulation-dependent enhancer activity, including an IL2RA enhancer that harbors an autoimmunity risk variant. Using engineered mouse models and genome editing of human primary T cells, we found that sequence perturbation of the disease-associated IL2RA enhancer does not block IL2RA expression, but rather delays the timing of gene activation in response to specific extracellular signals. This work develops an approach to rapidly identify functional enhancers within non-coding regions, decodes a key human autoimmunity association, and suggests a general mechanism by which genetic variation can cause immune dysfunction.

genetics↗

bioRxiv2016

Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) and RNA-seq profiles from activated CD4+ T cells of up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, in patterns consistent with the 3D organization of chromosomes measured by in situ Hi-C in T cells. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak through disrupting binding sites for transcription factors important for T cell differentiation and activation. These ATAC quantitative trait nucleotides (ATAC-QTNs) have the largest effects on co-accessible peaks, are associated with gene expression from the same aliquot of cells, are rarely affecting core binding motifs, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis- regulatory elements, in isolation or in concert, to influence gene expression in primary immune cells that play a key role in many human diseases.

genomics↗